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On-Stack Replacement (OSR) is a technique that allows to interrupt halt  the execution of a function and continue from the same program state with a different version of the function. OSR is often used in virtual machines to interrupt a long-running function and recompile it at a higher optimization level, or to invalidate no longer holding replace it with a different one when a  speculative assumptions assumption  made during the its  compilation of that function. no longer holds.  In this paper we present a novel framework to perform OSR transitions. Compared to extant OSR techniques, our approach is platform-independent as transitions are encoded entirely at the Intermediate Representation (IR) level, level;  it supports OSR-point insertion at arbitrary locations in a function, and it allows a function version reached via OSR to fire an OSR itself, either to a more optimized version or to a less optimized one from which it was derived. We implement and evaluate our technique in the LLVM compiler infrastructure, which is nowadays being increasingly used as Just-In-Time (JIT) compiler inseveral  virtual machines for dynamic languages such as Javascript, MATLAB, Python and Ruby. We thus then  present a case study on the integration of our technique in the McVM virtual machine for MATLAB, showing interesting speedups achieved  from the optimization of a popular construct of the language.